New Technologies - trends, innovations and research by Constantin Volosencu

By Constantin Volosencu

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Sun, Y. ; Lee, K. S. & Nee, A. Y. C. (2004). Design and FEM analysis of the milled groove insert method for cooling of plastic injection moulds. The International Journal of Advanced Manufacturing Technology 24(9), pp. 715-726. Tang, L. ; Chassapis, C. & Manoochehri, S. (1997). Optimal cooling system design for multicavity injection molding. Finite Elements in Analysis and Design 26(3), pp. 229-251. Wang, G. G. & Shan, S. (2007). Review of Metamodeling Techniques in Support of Engineering Design Optimization.

Different from direct simulation-based optimization method, the evaluating step needs to be done in order to verify the fidelity of the metamodel at the “optimum” point because it always exist an error between the metamodel and real response. In other words, there is an error between the predicted and actual values at the optimum point because metamodels are approximate models. If the error between the responses obtained by prediction and CAE simulation is acceptable or if it satisfies the designer, the optimization process is finished successfully.

Engineering Analysis with Boundary Elements 33(8-9), pp. 1022-1030. 3 Biologically Inspired Techniques for Autonomous Shop Floor Control Hong-Seok Park, Ngoc-Hien Tran and Jin-Woo Park University of Ulsan South Korea 1. Introduction Currently, the conventional manufacturing systems, such as the Flexible Manufacturing Systems (FMSs) are unable to adapt to the complexity and dynamic of the manufacturing environment. These systems activate the automatic operations by using the pre-instructed programs and should be stopped to re-program and re-plan in case of changes of the manufacturing environment, which reduce the flexibility of the systems and increase the downtime.

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